forked from Github/frigate
switch everything to run off of tracked objects
This commit is contained in:
Blake Blackshear
@@ -10,10 +10,9 @@ from scipy.spatial import distance as dist
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from frigate.util import draw_box_with_label, LABELS, compute_intersection_rectangle, compute_intersection_over_union, calculate_region
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class ObjectCleaner(threading.Thread):
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def __init__(self, objects_parsed, detected_objects):
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def __init__(self, camera):
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threading.Thread.__init__(self)
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self._objects_parsed = objects_parsed
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self._detected_objects = detected_objects
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self.camera = camera
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def run(self):
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prctl.set_name("ObjectCleaner")
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@@ -22,22 +21,9 @@ class ObjectCleaner(threading.Thread):
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# wait a bit before checking for expired frames
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time.sleep(0.2)
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# expire the objects that are more than 1 second old
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now = datetime.datetime.now().timestamp()
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# look for the first object found within the last second
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# (newest objects are appended to the end)
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detected_objects = self._detected_objects.copy()
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objects_removed = False
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for frame_time in detected_objects.keys():
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if now-frame_time>2:
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del self._detected_objects[frame_time]
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objects_removed = True
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if objects_removed:
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# notify that parsed objects were changed
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with self._objects_parsed:
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self._objects_parsed.notify_all()
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for frame_time in list(self.camera.detected_objects.keys()).copy():
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if not frame_time in self.camera.frame_cache:
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del self.camera.detected_objects[frame_time]
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class DetectedObjectsProcessor(threading.Thread):
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def __init__(self, camera):
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@@ -168,9 +154,6 @@ class RegionRefiner(threading.Thread):
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selected_objects = [o for o in selected_objects if not self.filtered(o)]
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self.camera.detected_objects[frame_time] = selected_objects
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with self.camera.objects_parsed:
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self.camera.objects_parsed.notify_all()
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# print(f"{frame_time} is actually finished")
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@@ -247,11 +230,16 @@ class ObjectTracker(threading.Thread):
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while True:
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frame_time = self.camera.refined_frame_queue.get()
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self.match_and_update(self.camera.detected_objects[frame_time])
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self.camera.frame_tracked_queue.put(frame_time)
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self.camera.frame_output_queue.put(frame_time)
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if len(self.tracked_objects) > 0:
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with self.camera.objects_tracked:
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self.camera.objects_tracked.notify_all()
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def register(self, index, obj):
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id = f"{str(obj['frame_time'])}-{index}"
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obj['id'] = id
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obj['top_score'] = obj['score']
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self.add_history(obj)
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self.tracked_objects[id] = obj
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self.disappeared[id] = 0
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@@ -261,7 +249,22 @@ class ObjectTracker(threading.Thread):
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def update(self, id, new_obj):
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self.tracked_objects[id].update(new_obj)
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# TODO: am i missing anything? history?
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self.add_history(self.tracked_objects[id])
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if self.tracked_objects[id]['score'] > self.tracked_objects[id]['top_score']:
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self.tracked_objects[id]['top_score'] = self.tracked_objects[id]['score']
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def add_history(self, obj):
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entry = {
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'score': obj['score'],
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'box': obj['box'],
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'region': obj['region'],
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'centroid': obj['centroid'],
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'frame_time': obj['frame_time']
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}
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if 'history' in obj:
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obj['history'].append(entry)
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else:
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obj['history'] = [entry]
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def match_and_update(self, new_objects):
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# check to see if the list of input bounding box rectangles
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@@ -384,26 +387,23 @@ class ObjectTracker(threading.Thread):
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# Maintains the frame and object with the highest score
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class BestFrames(threading.Thread):
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def __init__(self, objects_parsed, recent_frames, detected_objects):
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def __init__(self, camera):
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threading.Thread.__init__(self)
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self.objects_parsed = objects_parsed
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self.recent_frames = recent_frames
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self.detected_objects = detected_objects
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self.camera = camera
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self.best_objects = {}
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self.best_frames = {}
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def run(self):
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prctl.set_name("BestFrames")
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prctl.set_name(self.__class__.__name__)
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while True:
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# wait until objects have been parsed
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with self.objects_parsed:
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self.objects_parsed.wait()
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# wait until objects have been tracked
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with self.camera.objects_tracked:
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self.camera.objects_tracked.wait()
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# make a copy of detected objects
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detected_objects = self.detected_objects.copy()
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detected_objects = list(self.camera.object_tracker.tracked_objects.values()).copy()
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for obj in itertools.chain.from_iterable(detected_objects.values()):
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for obj in detected_objects:
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if obj['name'] in self.best_objects:
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now = datetime.datetime.now().timestamp()
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# if the object is a higher score than the current best score
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@@ -413,12 +413,9 @@ class BestFrames(threading.Thread):
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else:
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self.best_objects[obj['name']] = obj
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# make a copy of the recent frames
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recent_frames = self.recent_frames.copy()
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for name, obj in self.best_objects.items():
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if obj['frame_time'] in recent_frames:
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best_frame = recent_frames[obj['frame_time']] #, np.zeros((720,1280,3), np.uint8))
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if obj['frame_time'] in self.camera.frame_cache:
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best_frame = self.camera.frame_cache[obj['frame_time']]
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draw_box_with_label(best_frame, obj['box']['xmin'], obj['box']['ymin'],
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obj['box']['xmax'], obj['box']['ymax'], obj['name'], f"{int(obj['score']*100)}% {obj['area']}")
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